def draw_class_scatter_and_pie(locsfile,format='pdf',sps=None):
'''given a .mouselocs file
(and assuming .locsumm, .frame and .mice are present)
draws a .scatter.[format] and .pie.[format] summarizing the data in that segment
'''
def secs(x):
return '%0.1f sec' % ((x*sps)/100)
if sps is None:
match = re.search(r'\/([\d\.]+)sec_',locsfile)
if match:
sps = float(match.groups()[0])
else:
sps = 1.0
pylab.gray()
mice = eval(open(os.path.splitext(locsfile)[0]+'.mice').read())
locsumm = eval(open(os.path.splitext(locsfile)[0]+'.locsumm').read())
mouselocs = eval(open(locsfile).read())
bkgd_image = sorted(mice.keys())[0] # grabs first frame as background
sca_out = os.path.splitext(locsfile)[0]+'.scatter.'+format
pie_out = os.path.splitext(locsfile)[0]+'.pie.'+format
print >> sys.stderr, 'drawing pie (%s) and scatter (%s) with data from %s (%s frames, %s seconds per segment)' % \
(pie_out,sca_out,locsfile,len(mouselocs.keys()),sps)
class_locs = Util.invert_dict(mouselocs)
fig = pylab.figure(1,figsize=(9,6))
pylab.matshow(vidtools.load_normed_arrays([bkgd_image])[0],fignum=1)
fig.axes[0].set_xticks([])
fig.axes[0].set_yticks([])
counts = []
piecols = []
for act_class,frames in class_locs.items():
if act_class is None:
continue
coords = filter(None,[mice[f] for f in frames])
if (coords):
x,y = Util.dezip(coords)
pylab.scatter(x,y,c=col[act_class])
counts.append(len(frames))
piecols.append(col[act_class])
pylab.savefig(sca_out)
fig = pylab.figure(2,figsize=(6,6))
pylab.pie(counts,colors=piecols,autopct=secs )
pylab.savefig(pie_out)
def draw_class_scatter_and_pie(locsfile, format='pdf', sps=None):
'''given a .mouselocs file
(and assuming .locsumm, .frame and .mice are present)
draws a .scatter.[format] and .pie.[format] summarizing the data in that segment
'''
def secs(x):
return '%0.1f sec' % ((x * sps) / 100)
if sps is None:
match = re.search(r'\/([\d\.]+)sec_', locsfile)
if match:
sps = float(match.groups()[0])
else:
sps = 1.0
pylab.gray()
mice = eval(open(os.path.splitext(locsfile)[0] + '.mice').read())
locsumm = eval(open(os.path.splitext(locsfile)[0] + '.locsumm').read())
mouselocs = eval(open(locsfile).read())
bkgd_image = sorted(mice.keys())[0] # grabs first frame as background
sca_out = os.path.splitext(locsfile)[0] + '.scatter.' + format
pie_out = os.path.splitext(locsfile)[0] + '.pie.' + format
print >> sys.stderr, 'drawing pie (%s) and scatter (%s) with data from %s (%s frames, %s seconds per segment)' % \
(pie_out,sca_out,locsfile,len(mouselocs.keys()),sps)
class_locs = Util.invert_dict(mouselocs)
fig = pylab.figure(1, figsize=(9, 6))
pylab.matshow(vidtools.load_normed_arrays([bkgd_image])[0], fignum=1)
fig.axes[0].set_xticks([])
fig.axes[0].set_yticks([])
counts = []
piecols = []
for act_class, frames in class_locs.items():
if act_class is None:
continue
coords = filter(None, [mice[f] for f in frames])
if (coords):
x, y = Util.dezip(coords)
pylab.scatter(x, y, c=col[act_class])
counts.append(len(frames))
piecols.append(col[act_class])
pylab.savefig(sca_out)
fig = pylab.figure(2, figsize=(6, 6))
pylab.pie(counts, colors=piecols, autopct=secs)
pylab.savefig(pie_out)
ybounds = [int(i) for i in sys.argv[-2:]]
elif len(sys.argv) == 10:
mousezcut = float(sys.argv[7])
ybounds = [int(i) for i in sys.argv[-2:]]
else:
mousezcut = None
ybounds = None
print >> sys.stderr, 'summarizing frames %s to %s from %s. output to %s. Masked by %s and %s. Movement z score of %s, ybounds of %s' % (
start, stop, imagedir, outroot, maskfile, burrow_maskfile, mousezcut,
ybounds)
images = sorted(glob(imagedir + '/*.png'))[start:stop]
bkgd_images = sorted(glob(imagedir + '/*.png'))[stop:stop + (stop - start)]
frames = vidtools.load_normed_arrays(images, pixav)
#print >> sys.stderr, 'time averaging invoked, window of %s frames' % (timeav)
#frames = Util.zsmooth_convol(frames,timeav)
#windowed_frames = vidtools.average_frames(frames,num_wins=wins)
#frameav = vidtools.average_frames(windowed_frames)
'''
try:
frameav = vidtools.average_frames(bkgd_images,pixav)
except IndexError:
frameav = vidtools.average_frames(frames)
'''
frameav = vidtools.average_frames(frames)
SHAPE = frames[0].shape
micez_outfile = os.path.join( outroot,'%07d-%07d.micez' % (start,stop) )
micesize_outfile = os.path.join( outroot,'%07d-%07d.micesize' % (start,stop) )
micelen_outfile = os.path.join( outroot,'%07d-%07d.micelen' % (start,stop) )
if os.path.exists(outfile):
print >> sys.stderr, 'file %s present; skipping' % outfile
else:
print >> sys.stderr, 'summarizing frames %s to %s from %s. output to %s. Masked by %s. Movement z score of %s, xybounds of %s. Intensities averaged over %s pixels' % (start,stop,imagedir,outroot,maskfile,mousezcut,opts['xybounds'],pixav)
#transparent support for supplying a tarball in lieu of a directory; assumes the tarball is only images
if imagedir.endswith('.tar'):
import tarfile
imtar = tarfile.open(imagedir)
tarcont = sorted(imtar.getnames())[start:stop]
images = ['%s:%s' % (imagedir,f) for f in tarcont]
frames = vidtools.load_normed_arrays([imtar.extractfile(f) for f in tarcont],pixav)
else:
images = sorted(glob(imagedir+'/*.png'))[start:stop]
#new toys! image smoothing
SMOOTH5 = ImageFilter.Kernel( (5, 5) , (1,2,2,2,1,2,3,3,3,2,2,3,5,3,2,2,3,3,3,2,1,2,2,2,1 ) )
frames = vidtools.load_normed_arrays(images,img_smooth_kernel=SMOOTH5)
print >> sys.stderr, len(images),'images selected'
print >> sys.stderr, len(frames),'frames loaded'
exp_frames = int(stop) - int(start)
if len(frames) != exp_frames:
raise ValueError, 'expected %s frames, found %s' % (exp_frames,len(frames))
if maskfile == 'None':
mask = numpy.zeros(frames[0].shape,dtype=bool)
def draw_class_scatter_and_pie(locsfile,format='pdf',sps=None,scatter_lines=None,scatter_polys=None,draw_pie=True,shape=(480,720),poly_col=None):
'''given a .mouselocs file
(and assuming .locsumm, .frame and .mice are present)
draws a .scatter.[format] and .pie.[format] summarizing the data in that segment
if .ground or .actmask are present, these will be plotted as lines and polygons respectively
'''
def secs(x):
return '%0.1f sec' % ((x*sps)/100)
if sps is None:
match = re.search(r'\/([\d\.]+)sec_',locsfile)
if match:
sps = float(match.groups()[0])
else:
sps = 1.0
if scatter_polys is not None and poly_col is None:
poly_col = ['b']*len(scatter_polys)
pylab.gray()
print >> sys.stderr, 'loading mice'
mice = eval(open(os.path.splitext(locsfile)[0]+'.mice').read())
print >> sys.stderr, 'loading location summaries'
locsumm = eval(open(os.path.splitext(locsfile)[0]+'.locsumm').read())
print >> sys.stderr, 'loading locations'
mouselocs = eval(open(locsfile).read())
bkgd_image = sorted(mice.keys())[0] # grabs first frame as background
sca_out = os.path.splitext(locsfile)[0]+'.scatter.'+format
pie_out = os.path.splitext(locsfile)[0]+'.pie.'+format
if draw_pie:
print >> sys.stderr, 'drawing pie (%s) and scatter (%s) with data from %s (%s frames, %s seconds per segment)' % \
(pie_out,sca_out,locsfile,len(mouselocs.keys()),sps)
else:
print >> sys.stderr, 'drawing scatter (%s) with data from %s (%s frames, %s seconds per segment)' % \
(sca_out,locsfile,len(mouselocs.keys()),sps)
class_locs = Util.invert_dict(mouselocs)
fig = pylab.figure(1,figsize=(9,6))
fig.clf()
print >> sys.stderr, 'render:'
try:
bkgd_mat = vidtools.load_normed_arrays([bkgd_image])[0]
except:
print >> sys.stderr, '\timages unavailable, attempting with .frame'
frame = os.path.splitext(locsfile)[0]+'.frame'
bkgd_mat = numpy.fromfile(frame).reshape(shape)
print >> sys.stderr, '\tframe'
pylab.matshow(bkgd_mat,fignum=1)
fig.axes[0].set_xticks([])
fig.axes[0].set_yticks([])
if os.path.exists(os.path.splitext(locsfile)[0]+'.ground'):
ground = pylab.fromfile(os.path.splitext(locsfile)[0]+'.ground',sep='\n')
pylab.plot(ground,'g')
if os.path.exists(os.path.splitext(locsfile)[0]+'.actpoly'):
actpoly = eval(open(os.path.splitext(locsfile)[0]+'.actpoly').read())
#elif os.path.exists(os.path.splitext(locsfile)[0]+'.actmat'):
# actmat = numpy.fromfile(os.path.splitext(locsfile)[0]+'.actmat').reshape(bkgd_mat.shape)
# if ground:
# actmat = Util.subtract_mask(actmat,vidtools.mask_from_vector(ground+10,bkgd_mat.shape))
#attempt to draw activity polygons from actmasks directly is too much work at this step;
#supply scatter_polys or make sure an actpoly file is present
counts = []
piecols = []
print >> sys.stderr, '\tlines'
if isinstance(scatter_lines,list):
for l in scatter_lines:
pylab.plot(l)
print >> sys.stderr, '\tpolygons'
if isinstance(scatter_polys,list):
for i,p in enumerate(scatter_polys):
try:
fig.axes[0].add_patch(pylab.matplotlib.patches.Polygon(p,fc='none',ec=poly_col[i]))
except AssertionError:
print >> sys.stderr, 'poly %s improper dimensions' % p
print >> sys.stderr, '\tscatter'
for act_class,frames in class_locs.items():
if act_class is None:
continue
coords = filter(None,[mice[f] for f in frames])
if (coords):
x,y = Util.dezip(coords)
#pylab.scatter(x,y,s=10,c=col[act_class])
pylab.scatter(x,y,s=3,c='r',edgecolors='none')
counts.append(len(frames))
piecols.append(col[act_class])
pylab.savefig(sca_out)
if draw_pie:
print >> sys.stderr, '\tpie'
fig = pylab.figure(2,figsize=(6,6))
fig.clf()
pylab.pie(counts,colors=piecols,autopct=secs )
pylab.savefig(pie_out)
FORMAT='jpg'
print >> sys.stderr, '"jpg" found in path, assuming FORMAT=jpg\n'
else:
FORMAT='png'
match = re.search(r'\/([\d\.]+)fps\/',imagedir)
if match:
FPS = match.groups()[0]
else:
FPS = 30
images = sorted(glob(imagedir+'/*.'+FORMAT))
print >> sys.stderr, len(images),'images found in imagedir\n'
print >> sys.stderr, 'split, top and bottom XY:',splitxy,topxy,bottomxy
SHAPE=vidtools.load_normed_arrays(images[:1])[0].shape
match = re.search('(\d+)fps',imagedir)
if match:
segment_step = int(seglen)*int(match.groups()[0])
print >> sys.stderr, 'segment length will be %s frames (%s seconds, %s fps)\n' % (segment_step,seglen,match.groups()[0])
unit = 'sec'
else:
segment_step = int(seglen)
print >> sys.stderr,'fps could not be found in image path, using seglen (%s) as segment_step (i.e. 1 fps)\n' % seglen
unit = 'frames'
outroot = os.path.join(imagedir,'analysis','%s%s_%smousez' % (seglen,unit,mousez))
try:
os.makedirs(outroot)
for cnt,image in enumerate(mice.keys()):
if cnt%tickon == 0:
print >> sys.stderr, '%6d/%6d' % (cnt,len(mice))
im = os.path.split(image)[1]
n,ext = os.path.splitext(im)
n = int(n)
outf = os.path.join(an_im_dir,'%07d.png' % (n-startn))
#print >> sys.stderr, '\tdraw %s...' % outf,
if os.path.exists(outf):
#print >> sys.stderr, 'skip'
continue
#pylab.matshow(vidtools.load_normed_arrays([image])[0],fignum=1)
fig = pylab.figure(1)
fr = vidtools.load_normed_arrays([image])[0]
aspect = fr.shape[1]/float(fr.shape[0])
pylab.imshow(fr)
ax = pylab.figure(1).axes[0]
try:
pylab.plot(g,'g')
except:
pass
# out for now; if "mouseloc" concept returns, uncomment
#if mouselocs[image] and mice[image] is not None:
# lastcoord = Util.dezip([mice[image]])
# lastcol = col[mouselocs[image]]
# pylab.scatter(c=lastcol,*lastcoord)
micelen_outfile = os.path.join(outroot, '%07d-%07d.micelen' % (start, stop))
if os.path.exists(outfile):
print >> sys.stderr, 'file %s present; skipping' % outfile
else:
print >> sys.stderr, 'summarizing frames %s to %s from %s. output to %s. Masked by %s. Movement z score of %s, xybounds of %s. Intensities averaged over %s pixels' % (
start, stop, imagedir, outroot, maskfile, mousezcut, opts['xybounds'],
pixav)
#transparent support for supplying a tarball in lieu of a directory; assumes the tarball is only images
if imagedir.endswith('.tar'):
import tarfile
imtar = tarfile.open(imagedir)
tarcont = sorted(imtar.getnames())[start:stop]
images = ['%s:%s' % (imagedir, f) for f in tarcont]
frames = vidtools.load_normed_arrays(
[imtar.extractfile(f) for f in tarcont], pixav)
else:
images = sorted(glob(imagedir + '/*.png'))[start:stop]
#new toys! image smoothing
SMOOTH5 = ImageFilter.Kernel(
(5, 5), (1, 2, 2, 2, 1, 2, 3, 3, 3, 2, 2, 3, 5, 3, 2, 2, 3, 3, 3,
2, 1, 2, 2, 2, 1))
frames = vidtools.load_normed_arrays(images, img_smooth_kernel=SMOOTH5)
print >> sys.stderr, len(images), 'images selected'
print >> sys.stderr, len(frames), 'frames loaded'
exp_frames = int(stop) - int(start)
if len(frames) != exp_frames:
raise ValueError, 'expected %s frames, found %s' % (exp_frames,
len(frames))
elif len(sys.argv) == 9: mousezcut = None ybounds = [int(i) for i in sys.argv[-2:]] elif len(sys.argv) == 10: mousezcut = float(sys.argv[7]) ybounds = [int(i) for i in sys.argv[-2:]] else: mousezcut = None ybounds = None print >> sys.stderr, 'summarizing frames %s to %s from %s. output to %s. Masked by %s and %s. Movement z score of %s, ybounds of %s' % (start,stop,imagedir,outroot,maskfile,burrow_maskfile,mousezcut,ybounds) images = sorted(glob(imagedir+'/*.png'))[start:stop] bkgd_images = sorted(glob(imagedir+'/*.png'))[stop:stop+(stop-start)] frames = vidtools.load_normed_arrays(images,pixav) #print >> sys.stderr, 'time averaging invoked, window of %s frames' % (timeav) #frames = Util.zsmooth_convol(frames,timeav) #windowed_frames = vidtools.average_frames(frames,num_wins=wins) #frameav = vidtools.average_frames(windowed_frames) ''' try: frameav = vidtools.average_frames(bkgd_images,pixav) except IndexError: frameav = vidtools.average_frames(frames) ''' frameav = vidtools.average_frames(frames) SHAPE = frames[0].shape
def draw_class_scatter_and_pie(locsfile,
format='pdf',
sps=None,
scatter_lines=None,
scatter_polys=None):
'''given a .mouselocs file
(and assuming .locsumm, .frame and .mice are present)
draws a .scatter.[format] and .pie.[format] summarizing the data in that segment
if .ground or .actmask are present, these will be plotted as lines and polygons respectively
'''
def secs(x):
return '%0.1f sec' % ((x * sps) / 100)
if sps is None:
match = re.search(r'\/([\d\.]+)sec_', locsfile)
if match:
sps = float(match.groups()[0])
else:
sps = 1.0
pylab.gray()
mice = eval(open(os.path.splitext(locsfile)[0] + '.mice').read())
locsumm = eval(open(os.path.splitext(locsfile)[0] + '.locsumm').read())
mouselocs = eval(open(locsfile).read())
bkgd_image = sorted(mice.keys())[0] # grabs first frame as background
sca_out = os.path.splitext(locsfile)[0] + '.scatter.' + format
pie_out = os.path.splitext(locsfile)[0] + '.pie.' + format
print >> sys.stderr, 'drawing pie (%s) and scatter (%s) with data from %s (%s frames, %s seconds per segment)' % \
(pie_out,sca_out,locsfile,len(mouselocs.keys()),sps)
class_locs = Util.invert_dict(mouselocs)
fig = pylab.figure(1, figsize=(9, 6))
fig.clf()
bkgd_mat = vidtools.load_normed_arrays([bkgd_image])[0]
pylab.matshow(bkgd_mat, fignum=1)
fig.axes[0].set_xticks([])
fig.axes[0].set_yticks([])
if os.path.exists(os.path.splitext(locsfile)[0] + '.ground'):
ground = pylab.fromfile(os.path.splitext(locsfile)[0] + '.ground',
sep='\n')
pylab.plot(ground, 'g')
if os.path.exists(os.path.splitext(locsfile)[0] + '.actpoly'):
actpoly = eval(
open(os.path.splitext(locsfile)[0] + '.actpoly').read())
#elif os.path.exists(os.path.splitext(locsfile)[0]+'.actmat'):
# actmat = numpy.fromfile(os.path.splitext(locsfile)[0]+'.actmat').reshape(bkgd_mat.shape)
# if ground:
# actmat = Util.subtract_mask(actmat,vidtools.mask_from_vector(ground+10,bkgd_mat.shape))
#attempt to draw activity polygons from actmasks directly is too much work at this step;
#supply scatter_polys or make sure an actpoly file is present
counts = []
piecols = []
if isinstance(scatter_lines, list):
for l in scatter_lines:
pylab.plot(l)
if isinstance(scatter_polys, list):
for p in scatter_polys:
fig.axes[0].add_patch(
pylab.matplotlib.patches.Polygon(p, fc='none', ec='b'))
for act_class, frames in class_locs.items():
if act_class is None:
continue
coords = filter(None, [mice[f] for f in frames])
if (coords):
x, y = Util.dezip(coords)
pylab.scatter(x, y, s=10, c=col[act_class])
counts.append(len(frames))
piecols.append(col[act_class])
pylab.savefig(sca_out)
fig = pylab.figure(2, figsize=(6, 6))
fig.clf()
pylab.pie(counts, colors=piecols, autopct=secs)
pylab.savefig(pie_out)
